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GCP, Vertex AI, Gemini APIs,Python

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Onsite

GCP, Vertex AI, Gemini APIs,Python

Tata Consultancy Services

GCP, Vertex AI, Gemini APIs,Python

Skills

Google Cloud PlatformData EngineeringPythonMicroservicesMachine LearningAIKubernetes

1 month ago

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Important information


Contract type:

Permanent

Location:

India

Work mode:

Onsite

Published on:

28 September 2026

What they need


  • Must have 10+ years of software engineering experience with strong expertise in system design

and scalable architecture.

  • Must have extensive experience in Python, APIs, microservices, and cloud-native application development.
  • Must have 4+ years of hands-on experience with Google Cloud Platform (GCP), Vertex AI, Gemini APIs, Agent Builder,

and AI/ML platforms.

  • Must have experience designing and delivering enterprise AI solutions using LLMs, RAG,

multi-agent systems, and Agentic AI frameworks.

  • Must have experience leading customer-facing solution architecture, technical consulting,

and executive stakeholder engagements.

  • Must have experience building AI accelerators, reusable frameworks, PoCs, and production-grade AI applications.
  • Must have expertise in cloud architecture, Kubernetes, containerization, DevOps, CI/CD,

and platform engineering.

  • Must have strong experience in data engineering, vector databases, knowledge retrieval systems,

and AI governance.

Roles & Responsibilities

  • Lead the solution architecture and technical strategy for enterprise AI and cloud transformation initiatives.
  • Engage with customers and business stakeholders to translate business challenges into scalable AI solutions.
  • Design and oversee the development of AI-powered applications leveraging Gemini, Vertex AI, and Google Cloud services.
  • Build and drive complex AI architectures involving RAG, Agentic AI, multimodal AI, and enterprise integrations.
  • Lead technical discovery sessions, workshops, PoCs, and customer demonstrations.
  • Mentor engineering teams and establish best practices for AI engineering and cloud-native development.
  • Collaborate with product, engineering, sales, and partner teams to accelerate AI adoption and business outcomes.
  • Define technical roadmaps, governance standards, and operational models for enterprise-scale AI deployments.
  • Stay current with emerging AI technologies and apply them to customer scenarios

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